Emerging applications, like deep neural networks, use massive computational and memory abilities to train on different datasets and learn with high accuracy. Moreover, as applications like high-performance computing (HPC), graphics algorithms, etc., become data- and compute-intensive, energy-efficiency and low latency become critical characteristics. Processing in memory (PIM) has the ability to address these challenges by scheduling complex operations on DRAM logic dies to provide additional compute abilities in a lower-power technology process and also closer to where the data is located.